Strategic advice to leverage new technologies
Technology is at the heart of nearly every enterprise, enabling new business models and strategies, and serving as the catalyst to industry convergence. Leveraging the right technology can improve business outcomes, providing intelligence and insights that help you make more informed and accurate decisions. From finding patterns in data through data science, to curating relevant insights with data analytics, to the predictive abilities and innumerable applications of AI, to solving challenging business problems with ML, NLP, and knowledge graphs, technology has brought decision-making to a more intelligent level. Keep pace with the technology trends, opportunities, applications, and real-world use cases that will move your organization closer to its transformation and business goals.
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Although recent advances in computing user interfaces for decision support tools make the tools much easier to learn, understand, and manipulate, some decision makers may be reluctant to adopt and use a new decision support tool. Potential users with greater IT knowledge and expertise often find it easier to learn new systems than those who are infrequent users and hence lack knowledge and expertise. Thus, developers should strive to build a decision support capability that targets potential users, matching the design to user needs, abilities, and skills.
Managing Objects
In statistical project management (SPM), we simplify the project management approach by eliminating many concepts that the dominant project management methodologies consider central. Objects represent a repeatable thing that non-IT people can wrap their minds around. They are supposed to be concrete, like a balance sheet report in an accounting system or an employee demographics data-entry Web form. Since objects are supposed to be repeatable, project managers and the IT organization would find it very helpful to know how long, on average, it takes teams to create and operate related objects. Thus, objects become an important list of deliverables and one that is crucial to estimate accurately. Objects represent, from the user’s perspective, the list of things that are delivered to them — a kind of a bill of materials.
Software architecture requires balance. During the 20 years I’ve been leading technology organizations to build products, mostly via Agile, I’ve learned some rules that have helped me — and my teams — successfully strike the right balance. These aren’t technically focused rules; they’re more generic, so they apply to monolithic, layered, service-oriented, and microservice architectures equally well. One of these rules is the subject of this Advisor.
Dissent and the Art of “Hype-Cycle” Maintenance
Continuous dissent is necessary and extremely valuable — but also incredibly tough for the architect to participate in. This Executive Update seeks to find a balance that allows architects to engage in dissent while preserving their careers — and their sanity.
According to our latest research, one of biggest issues impeding organizations from carrying out their customer experience (CX) management initiatives is a lack of CX professionals within the organization. So how are organizations meeting or planning to meet their CX implementation needs?
Understanding data storage requires understanding data. Data sources, data types, storage sophistication, the structure and format associated with data, volume and velocity, meaningful processing, and, eventually, presentation of the results are all aspects of understanding data. Coupled with security, privacy, and quality, these factors play a pivotal role in delivering business value. This Executive Update investigates the relevance of NoSQL databases in providing business value.
Smart automation is most effective when humans and machines work together to deliver desired outcomes. Effective design for automation is not only about how much can be automated but should also consider how automation works together with humans to deliver value. Several fallacies observed in smart automation initiatives across industries can lead to failed initiatives that never see the light of day or that never deliver the promised outcomes. One fallacy that has led to such failures is the belief that all human activities can be automated.
This article takes us into another unexpected domain: production of energy resources. It is not obvious at the outset how embracing an Agile mindset might alter energy resource production rates, so his recounting of this story is especially interesting.